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GECCO
2007
Springer
179views Optimization» more  GECCO 2007»
13 years 12 months ago
Evolutionary selection of minimum number of features for classification of gene expression data using genetic algorithms
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
Alper Küçükural, Reyyan Yeniterzi...
GREC
2007
Springer
13 years 9 months ago
ARG Based on Arcs and Segments to Improve the Symbol Recognition by Genetic Algorithm
In this paper a genetic matching scheme is extended to take into account primitive arcs and complex description in the pattern recognition process. Classical ways only focus on seg...
J.-P. Salmon, Laurent Wendling
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
13 years 12 months ago
A NSGA-II, web-enabled, parallel optimization framework for NLP and MINLP
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time con...
David J. Powell, Joel K. Hollingsworth
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 9 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
ICANN
2003
Springer
13 years 11 months ago
Confidence Estimation Using the Incremental Learning Algorithm, Learn++
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
Jeffrey Byorick, Robi Polikar